Thesis title: Searching for New Physics in Run-2 dijet events with an eye on HL-LHC
Search for New Phenomena and new particles is one of the important goals of the current experimental programme at the Large Hadron Collider. The existence of new resonances could indeed describe a list of unexplained observations.
This thesis presents a search for New Physics in final states with two hadronic jets, using the data collected by the ATLAS experiment during the so-called LHC Run2 period. Dijet system invariant mass and angular distributions are compared to Standard Model predictions and used to probe both resonant and non resonant anomalies. The most recent results will be presented.
In the near future the ATLAS experiment will undergo an upgrade program in order to improve sensitivity to New Physics as much as possible. The detector in particular will be upgraded to withstand the challenging conditions expected for the High Luminosity phase of the LHC collider. Redesigning the trigger system of the experiment is crucial to maintain and possibly increase the detector performance. The muon trigger system upgrade will therefore be discussed in this work, with a particular focus to the main algorithm that will be implemented on the new FPGA-based hardware. A proposal for the adoption of novel Machine-Learning-based algorithms is presented.